T23.9 - An MILP Approach for Modeling and Analyzing the BESS for Smoothing Renewable Fluctuations Considering BESS Capacity Attenuation in the Bulk Power System with High Inverter-Based Resource Penetration

Analyzing the effectiveness of the battery energy storage system (BESS) on smoothing renewable fluctuations correctly is vital to the stable operation of the power system. Based on statistical programming and attention-based time series forecasting with learnable and interpretable basis (BasisFormer), we propose a mixed integer linear programming (MILP) approach for modeling and analyzing the BESS for smoothing renewable fluctuations in the bulk power system with high inverter-based resources. The approach considers BESS capacity attenuation and renewable uncertainty. First, we present a scenario generation and reduction method based on Latin hypercube sampling (LHS) and the Kantorovich distance. Second, we propose a BasisFormer-based BESS state of health (SoH) prediction method. Third, we establish a model of analyzing the BESS. Finally, we testify the proposed approach through case studies. The experimental results show that BESS capacity attenuation is a crucial factor in correctly analyzing the BESS effectiveness on smoothing renewable fluctuations.